Kang Boz

254 posts

Kang Boz

Kang Boz

@kangsboz

Katılım Kasım 2022
584 Takip Edilen170 Takipçiler
Kang Boz retweetledi
Dan
Dan@Daniel_Farinax·
Beginner video: How to install & use Grok Build (made for non-technical SuperGrok and X Premium+ users) I got so many questions from friends, so I made this simple step-by-step guide. You’ll see exactly how to: • Install Grok Build in seconds with one command • Create real websites • Use Grok Imagine to auto-generate images & videos • Run multiple projects at once in different folders Grok even runs commands for you. No coding experience needed. Watch the full walkthrough 👇
xAI@xai

Grok Build is now available in Beta for all SuperGrok and X Premium+ users. Use Plan Mode, create images and videos with Imagine, and build automations or orchestrators with the CLI. Visit x.ai/cli to get started.

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X Freeze
X Freeze@XFreeze·
Grok is now #1 on the AI Investing leaderboard, making real money at @ralliesai 8 models....$100,000 each Full freedom to trade After one month, Grok 4 leads with a +5.7% return Outperforming the newly released GPT-5.2 and Claude Opus 4.5 in live markets Grok is proving itself with real money on the line
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Noah Frydberg | Tiktok Shop For Brands
We replaced a $400K/year marketing team with 24 TikTok Shop AI Agents. We built a fully automated system that repurposes, localizes, and launches winning TikTok Shop content across hundreds of creator-style accounts. It’s so effective it feels like running Facebook ads in 2008. - CPMs as low as $0.10 - no reliance on paid ads - no ghost creators - no wasted samples - no lost time My $300/monthly tech stack which replaced $50k+ budget: - manus for product research and viral script ideas - nano banana pro for images - creatify for video - now testing reel farm for static images + automated posting (or use VAs) Here’s how it works: •Each AI Agent spins up a TikTok Shop–ready profile, built to sell my products through shoppable videos. •Agents are prompted to research the niche, scrape winning TikTok Shop videos, and rebuild them with new hooks, angles, and UGC-style visuals tailored to your brand. •They create and post daily using my tech stack onto affiliate accounts No touchpoints. No delays. Just shoppable videos going live and GMV compounding every week. Then we use an MPS (Multi-Platform Swarm) approach: once the concept works on TikTok Shop, we deploy hundreds of AI Agents to flood the niche with variations that all drive back to your Shop. I’m giving you access to the full stack — all 24 AI Agents, ready to plug into your TikTok Shop workflow today. Comment “Agent” and I’ll send you everything. (must be following) PS – Repost for early access to the full 24-Agent TikTok Shop system.
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Samruddhi Mokal
Samruddhi Mokal@samruddhi_mokal·
Gemini 3 has a capability most people don't even know exists. it's not the 1M tokens. it's not the multimodal processing. it's something else entirely. And it's the reason I built 3,000+ prompts specifically for Gemini 3. Everyone talks about Gemini's specs: → 1 million token context → Native multimodal inputs → Deep Think mode → Agentic workflows But they're missing what happens when you combine these features. The secret is persistent systems thinking. Gemini 3 doesn't just process large contexts. It maintains coherent reasoning ACROSS those contexts while simultaneously: - Analyzing images - Reading documents - Planning multi-step workflows - Adapting based on previous outputs This creates emergent capabilities that don't exist in other models. I built 3,000+ prompts that exploit this. Each prompt is built around this core insight: Gemini 3's real power isn't WHAT it can process. It's HOW it connects everything together. The library includes: ✓ 3,000+ production-ready prompts ✓ Organized by difficulty (beginner → advanced) ✓ Real use cases for each prompt Like, RT + reply "GEMINI" and I'll DM you the guide. (Must be following so I can DM) Skip this and keep wondering why your Gemini results feel the same as ChatGPT. Or grab the library and start using the capability everyone's missing.
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Nishan Chowdury
Nishan Chowdury@Nishan_011·
Nano Banana + MakeUGC + Veo3 = AI content Factory This agent pumps out hundreds of ads daily — fully automated. - No $300 creators - No $10K/month agency fees - No products Comment “Nano” and I'll send it for FREE! (must be following)
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Cas.Fyn
Cas.Fyn@FynCas·
Nano banana Pro + MakeUGC + Veo3 = Ad Factory This agent creates 200s of ads every day - UGC cost: $0 - Production time: minutes - Scale: instant You're able to re-create your competitors ads with AI Paste there ad -> Pick an avatar and regenerate. Comment "PRO" and I'll send you the agent + the full playbook (must be following)
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Vikram Verma
Vikram Verma@VikramVerm25510·
$345K in 35 days. No add agency, no freelancer. No creative team. Just 1 tool that spits out 348+ videos/day while we sleep. 400+ TikToks auto-posted daily 30 burner accounts 100% organic traffic Comment “ Ai Mass” & I’ll send the tool. (Must be following)
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Sirio Berati
Sirio Berati@heysirio_ai·
Wan 2.2 Animate is CRAZY and it actually excels at 3 things from my tests: 1. Lip syncing (so far the best open source I have seen, beating Runway Act2) 2. Consistent lighting & shadows with color tone replication when you swap a character 3. It keeps the replacement character aligned with realistic body dynamics even beyond the face. It is great for full body replacement
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Bunsan
Bunsan@BunsanXBT·
In Seoul, perp trading is an e-sport 1001x leverage isn’t enough ammo. Respawn after liquidation. The thrill is real.
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William | IA
William | IA@ia_william·
ChatGPT + 1 hour = $5,650 per month. My 14-year-old brother literally does this. Here are the 3 simple steps to follow to $5,650 per month ↓
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Bitcoin Junkies
Bitcoin Junkies@BitcoinJunkies·
JUST IN: 🇺🇸 Fed Chair Jerome Powell to deliver speech tomorrow at 8:30 AM EST.
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Lookonchain
Lookonchain@lookonchain·
A Bitcoin OG holding at least 80,009 $BTC($8.69B) woke up after 14+ years of dormancy and transferred out 40,000 $BTC($4.35B) today! This OG controls about 8 wallets, 2 of which received 20,000 $BTC($15,600 at the time, $2.18B now) on April 2, 2011, when the price of $BTC was 0.78. The other 6 wallets received 60,009 $BTC($202K at the time, $6.52B now) on May 4, 2011, when the price of $BTC was $3.37. Today, 4 wallets transferred out 40,000 $BTC, while 4 more wallets remain dormant. Address: 1KbrSKrT3GeEruTuuYYUSQ35JwKbrAWJYm 12tLs9c9RsALt4ockxa1hB4iTCTSmxj2me 1P1iThxBH542Gmk1kZNXyji4E4iwpvSbrt 1CPaziTqeEixPoSFtJxu74uDGbpEAotZom 1f1miYFQWTzdLiCBxtHHnNiW7WAWPUccr 1BAFWQhH9pNkz3mZDQ1tWrtKkSHVCkc3fV 14YK4mzJGo5NKkNnmVJeuEAQftLt795Gec 1ucXXZQSEf4zny2HRwAQKtVpkLPTUKRtt
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ₕₐₘₚₜₒₙ
ₕₐₘₚₜₒₙ@hamptonism·
MIT’s Entire Portfolio Management Lecture:
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DAN KOE
DAN KOE@thedankoe·
The easiest way to get ahead in life is to commit to a period of skill development. 6-12 months. Pure focus for 2-4 hours a day. Learning and building. Not just binge watching tutorials, but creating quality projects that you, others, or businesses could actually benefit from. Most people won't do it but those who do launch ahead of everyone else.
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FearBuck
FearBuck@FearedBuck·
UCLA graduate celebrates by showing off the ChatGPT he used for his final projects right before officially graduating 😭
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Artificial Analysis
Artificial Analysis@ArtificialAnlys·
MiniMax launches their first reasoning model: MiniMax M1, the second most intelligent open weights model after DeepSeek R1, with a much longer 1M token context window @minimax_ai M1 is based on their Text-01 model (released 14 Jan 2025) - an MoE with 456B total and 45.9B active parameters. This makes M1’s total parameter count smaller than DeepSeek R1’s 671B total parameters but larger than Qwen3 235B-A22B. Both Text-01 and M1 only support text input and output. MiniMax M1 80K scores 63 on the Artificial Analysis Intelligence Index. This lags DeepSeek R1 0528, but is slightly ahead of Alibaba’s Qwen3 235B-A22B and NVIDIA’s Llama 3.1 Nemotron Ultra. MiniMax M1 is offered in two variants: M1 40K and M1 80K, offering 40k and 80k token thinking budgets respectively. MiniMax discloses that their full RL training on Text-01 to create M1 used 512 H800 GPUs for three weeks - equivalent to a rental cost of $0.53M. This number is an interesting datapoint for the current degree of scaling of reinforcement learning. We note that it is not comparable to DeepSeek’s famous $5.6M training cost claim for DeepSeek V3, as DeepSeek’s number referred to full pre-training of the model not the reinforcement learning step. MiniMax offers models across multiple modalities on their Talkie app and API, including their Artificial Analysis Speech Leaderboard topping Speech-02 model, and Video models (T2V-01, and I2V-01). MiniMax M1 is the first of five announcements in their MiniMax Week. Availability: ➤ MiniMax M1 is available via MiniMax’s first-party API, priced at $0.4/$2.1 per 1M input/output tokens for ≤200k input tokens. The price increases to $1.2/$2.1 per 1M input/output tokens for >200k input tokens ➤ M1 is also currently available on @Novita, priced at $0.55/$2.2 per 1M input/output tokens with a 128k token context window ➤ M1 40k and M1 80k are both open weights models released under the Apache 2.0 license and we expect to see more third-party APIs supporting these models
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Python Developer
Python Developer@PythonDvz·
How to start learning ai Agents!
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Setya Mickala
Setya Mickala@setyamickala·
🧵 How Chinese and Korean traders farm @binance Alpha Points – a thread 1. While some in the Indonesian CT scene say: > “Devs cari users bukan gembel,” But the reality is: Many so-called “users” are simply treating the community as exit liquidity. Binance users, in particular, often sell their entire token holdings down to zero. Let’s break down how the Chinese traders are doing it 👇 2. I’ll tag @binance to show how some Chinese wallets are farming Alpha using a very structured method. 3. Here's what they do: 🔹 Set slippage to 0.01%, 0.03%, or 0.05% 🔹 Load wallet with $1,000 – $1,500 USDT 🔹 Swap: USDT → KOGE 🔹 Then KOGE → ZKJ (no need to swap back to USDT) 🔹 Repeat swapping KOGE ↔ ZKJ , ZKJ ↔ KOGE up to 10x - 11x Result: $10K–$16K in volume with $3 in daily fees. 4. Why are KOGE & ZKJ so stable? The stability of KOGE / ZKJ comes from concentrated liquidity in a single pool: KOGE-ZKJ. Chinese traders consistently add liquidity only to this pool, as it captures the majority of trading volume. They tend to avoid other tokens due to high fees and significant price volatility. 5. Essentially, they’re wash trading, but only between two tokens: KOGE ↔ ZKJ , ZKJ ↔ KOGE and will count for volume They’ve turned these two into a farming loop with minimal risk and stable prices. 6. On Alpha Market, they even use limit orders to minimize fee: 🔹 Buy ZKJ at 2.00910 🔹 Sell at 2.00950 Almost no loss.. 7. Why does the volume not flow into other tokens? Because only ZKJ & KOGE are perceived as safe for this strategy. Other tokens = high fees + risk of dumping. 8. How much longer will this cycle continue? Farmer from chinese join, take what they can, dump their bags, and leave , while pretending to be part of the community. When does it stop? Binance Alpha looks advanced, but it’s easily manipulated by a certain group. They generate fake volume with low fees on wash trade. No wonder so many Chinese farmers exploit it, Binance lets it happen to make the volume look real.
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